Open Access with author pays model: heading for the next serials crisis
Internet Health 2003;2:5
The serials crisis- or the serials pricing crisis is now into the fourth decade. The crisis brought about by the rising prices of journals and the decreasing subscriptions have been badly affecting researchers' access to vital scholarly communication. Discussions on how to circumvent this have taken a new perspective with the advent of electronic publishing, as a media capable of drastically cutting the cost of publishing [1]
Though electronic publishing has the potential to drastically bring down the cost of publication, and distribution of copies are virtually cost-free, there is some amount of fixed costs involved -for quality assurance in the form of review, editing and production of the first copy
How do Zimbabweans value health states?
Population Health Metrics 2003, 1:11 (published 16 December 2003)Background
Quality of life weights based on valuations of health states are often used in cost utility analysis and population health measures. This paper reports on an attempt to develop quality of life weights within the Zimbabwe context.
Methods
2,384 residents in randomly selected small residential plots of land in a high-density suburb of Harare valued descriptors of 38 health states based on different combinations of the five domains of the EQ-5D (mobility, self-care, usual activities, pain or discomfort and anxiety or depression). The English version of the EQ-5D was used. The time trade-off method was used to determine the values, and 19,020 individual preferences for health states were analysed. A residual maximum likelihood linear mixed model was used to estimate a function for predicting the values of all possible combinations of levels on the five domains. The model was fit to a random subset of two-thirds of the observations, with the remaining observations reserved for analysis of predictive validity. The results were compared to a similar study undertaken in the United Kingdom.
Results
A credible model was developed to predict the values of states that were not valued directly. In the subset of observations reserved for validation, the mean absolute difference between predicted and observed values was 0.045. All domains of the EQ-5D were found to contribute significantly to the model, both at the moderate and severe levels. Severe pain was found to have the largest negative coefficient, followed by the inability to wash and dress oneself.
Conclusion
Despite a generally lower education level than their European counterparts, urban Zimbabweans appear to value health states in a consistent manner, and the determination of a global method of establishing quality of life weights may be feasible and valid. However, as the relative weightings of the different domains, although correlated, differed from the standard set of weights recommended by the EuroQol Group, the locally determined coefficients should be used within the Zimbabwean context.
Generalized cost-effectiveness analysis for national-level priority-setting in the health sector
Cost Effectiveness and Resource Allocation 2003, 1:8 (published 19 December 2003)
Abstract
Cost-effectiveness analysis (CEA) is potentially an important aid to public health decision-making but, with some notable exceptions, its use and impact at the level of individual countries is limited. A number of potential reasons may account for this, among them technical shortcomings associated with the generation of current economic evidence, political expediency, social preferences and systemic barriers to implementation. As a form of sectoral CEA, Generalized CEA sets out to overcome a number of these barriers to the appropriate use of cost-effectiveness information at the regional and country level. Its application via WHO-CHOICE provides a new economic evidence base, as well as underlying methodological developments, concerning the cost-effectiveness of a range of health interventions for leading causes of, and risk factors for, disease.
The estimated sub-regional costs and effects of different interventions provided by WHO-CHOICE can readily be tailored to the specific context of individual countries, for example by adjustment to the quantity and unit prices of intervention inputs (costs) or the coverage, efficacy and adherence rates of interventions (effectiveness). The potential usefulness of this information for health policy and planning is in assessing if current intervention strategies represent an efficient use of scarce resources, and which of the potential additional interventions that are not yet implemented, or not implemented fully, should be given priority on the grounds of cost-effectiveness.
Health policy-makers and programme managers can use results from WHO-CHOICE as a valuable input into the planning and prioritization of services at national level, as well as a starting point for additional analyses of the trade-off between the efficiency of interventions in producing health and their impact on other key outcomes such as reducing inequalities and improving the health of the poor.
Reconsidering the use of rankings in the valuation of health states: a model for estimating cardinal values from ordinal data
Population Health Metrics 2003, 1:12 (published 19 December 2003)Abstract
Background
In survey studies on health-state valuations, ordinal ranking exercises often are used as precursors to other elicitation methods such as the time trade-off (TTO) or standard gamble, but the ranking data have not been used in deriving cardinal valuations. This study reconsiders the role of ordinal ranks in valuing health and introduces a new approach to estimate interval-scaled valuations based on aggregate ranking data.
Methods
Analyses were undertaken on data from a previously published general population survey study in the United Kingdom that included rankings and TTO values for hypothetical states described using the EQ-5D classification system. The EQ-5D includes five domains (mobility, self-care, usual activities, pain/discomfort and anxiety/depression) with three possible levels on each. Rank data were analysed using a random utility model, operationalized through conditional logit regression. In the statistical model, probabilities of observed rankings were related to the latent utilities of different health states, modeled as a linear function of EQ-5D domain scores, as in previously reported EQ-5D valuation functions. Predicted valuations based on the conditional logit model were compared to observed TTO values for the 42 states in the study and to predictions based on a model estimated directly from the TTO values. Models were evaluated using the intraclass correlation coefficient (ICC) between predictions and mean observations, and the root mean squared error of predictions at the individual level.
Results
Agreement between predicted valuations from the rank model and observed TTO values was very high, with an ICC of 0.98, only marginally lower than for predictions based on the model estimated directly from TTO values (ICC=0.99). Individual-level errors were also comparable in the two models, with root mean squared errors of 0.503 and 0.496 for the rank-based and TTO-based predictions, respectively.
Conclusions
Modeling health-state valuations based on ordinal ranks can provide results that are similar to those obtained from more widely analyzed valuation techniques such as the TTO. The information content in aggregate ranking data is not currently exploited to full advantage. The possibility of estimating cardinal valuations from ordinal ranks could also simplify future data collection dramatically and facilitate wider empirical study of health-state valuations in diverse settings and population groups.